GOAL OPTIMIZATIONMODEL DISCOVERYVARIABLE SELECTION& FILE SCORING

TheGmax empowers computers to model data without the need to tell them what to do or how to do it.

Say goodbye to regression, neural nets, genetic algorithms and other machine learners. TheGmax can reduce thousands of variables to a handful of key drivers in minutes while simultaneously discovering the formulae and rules that deliberately optimize user goals in a single step.

Missing information and mixed-data-types are perfectly acceptable. TheGmax truly represents a step change in the ability to rapidly mine and model data sets of any size and style.

Models so evolved are non-parametric, assumption free, immune to missing data, resistant to noise, unaffected by outliers and have unparalleled predictive power.

Goal Optimization

The freedoms gained by letting the data dictate its own model structure permit the deliberate targeting of non-parametric and rank-based objectives with the same ease that conventional methods minimise squared error.

TheGmax can explicitly optimize:

Areas under ROC curves

Multiple category discrimination

Cumulative lift indexes

Order based measures of entropy

Measures of rank correlation

Variable Selection

The most powerful auto-emergent property exhibited by TheGmax is its ability to automatically identify the key components and patterns in huge data sets.

Irrespective of whether there are 10 or 10,000 variables, the time required to identify the key drivers is unaffected. The process is very fast, thorough and efficient.

Some people use TheGmax for this feature alone.

File Scoring

This is where TheGmax earns its keep by putting the discovered models to work.

The value of a model lies in its ability to make predictions and the built-in companion utility, Gscore, is the productivity tool that automatically makes the predictions for you.